First of all, thanks for taking the initiative of bringing epigenomic analyses to the python programing environment. Together with scanpy, it has the potential of performing large scale multiomics projects without having to switch back and fort to R, making it easier to handle dependencies.
When reading the documentation though, I was quite disappointed to see that at the current status, episcanpy is not as complete as scanpy (barely any documentation nor notebooks, few processing and plotting functions), nor offers basic downstream analyses after integration like for example ArcheR does (TF footprinting, genome browser, differential accessible peak analysis, motif enrichment, peak2gene links and so on).
Are there any plans on extending episcanpy in the future? Unfortunately, right now it does not have enough functionality to justify using it. It would be a pity if these features were to be omitted since episcanpy has the potential to make the whole scanpy suite more attractive, especially now that multiome data-sets are more and more common.
Dear episcanpy team,
First of all, thanks for taking the initiative of bringing epigenomic analyses to the python programing environment. Together with scanpy, it has the potential of performing large scale multiomics projects without having to switch back and fort to R, making it easier to handle dependencies.
When reading the documentation though, I was quite disappointed to see that at the current status, episcanpy is not as complete as scanpy (barely any documentation nor notebooks, few processing and plotting functions), nor offers basic downstream analyses after integration like for example ArcheR does (TF footprinting, genome browser, differential accessible peak analysis, motif enrichment, peak2gene links and so on).
Are there any plans on extending episcanpy in the future? Unfortunately, right now it does not have enough functionality to justify using it. It would be a pity if these features were to be omitted since episcanpy has the potential to make the whole scanpy suite more attractive, especially now that multiome data-sets are more and more common.